A Recommendation Framework Based on the Analytic Network Process and its Application in the Semantic Technology Domain

When users face a certain problem needing a product, service, or action to solve it, selecting the best alternative among them can be a dicult task due to the uncertainty of their quality. This is especially the case in the domains where users do not have an expertise, like for example in Software Engineering. Multiple criteria decision making (MCDM) methods are methods that help making better decisions when facing the complex problem of selecting the best solution among a group of alternatives that can be compared according to different conflicting criteria. In MCDM problems, alternatives represent concrete products, services or actions that will help in achieving a goal, while criteria represent the characteristics of these alternatives that are important for making a decision.

Collaborative semantic editing of linked data lexica.

The creation of language resources is a time-consuming process requiring the efforts of many people. The use of resources collaboratively created by non-linguists can potentially ameliorate this situation. However, such resources often contain more errors compared to resources created by experts. For the particular case of lexica, we analyse the case of Wiktionary, a resource created along wiki principles and argue that through the use of a principled lexicon model, namely lemon, the resulting data could be better understandable to machines. We then present a platform called lemon source that supports the creation of linked lexical data along the lemon model. This tool builds on the concept of a semantic wiki to enable collaborative editing of the resources by many users concurrently. In this paper, we describe the model, the tool and present an evaluation of its usability based on a small group of users.

Exploring cognition processes in second language acquisition: the case of cognates and false-friends in EST

This article explores one aspect of the processing perspective in L2 learning in an EST context: the processing of new content words, in English, of the type ‘cognates’ and ‘false friends’, by Spanish speaking engineering students. The paper does not try to offer a comprehensive overview of language acquisition mechanisms, but rather it is intended to review more narrowly how our conceptual systems, governed by intricately linked networks of neural connections in the brain, make language development possible, creating, at the same time, some L2 processing problems. The case of ‘cognates and false friends’ in specialised contexts is brought here to illustrate some of the processing problems that the L2 learner has to confront, and how mappings in the visual, phonological and semantic (conceptual) brain structures function in second language processing of new vocabulary. Resumen Este artículo pretende reflexionar sobre un aspecto de la perspectiva del procesamiento de segundas lenguas (L2) en el contexto del ICT: el procesamiento de palabras nuevas, en inglés, conocidas como “cognados” y “falsos amigos”, por parte de estudiantes de ingeniería españoles. No se pretende ofrecer una visión completa de los mecanismos de adquisición del lenguaje, más bien se intenta mostrar cómo nuestro sistema conceptual, gobernado por una complicada red de conexiones neuronales en el cerebro, hace posible el desarrollo del lenguaje, aunque ello conlleve ciertas dificultades en el procesamiento de segundas lenguas. El caso de los “cognados” y los “falsos amigos”, en los lenguajes de especialidad, se trae para ilustrar algunos de los problemas de procesamiento que el estudiante de una lengua extranjera tiene que afrontar y el funcionamiento de las correspondencias entre las estructuras visuales, fonológicas y semánticas (conceptuales) del cerebro en el procesamiento de nuevo vocabulario.

Structuring research methods and data with the research object model: genomics workflows as a case study

Background: One of the main challenges for biomedical research lies in the computer-assisted integrative study of large and increasingly complex combinations of data in order to understand molecular mechanisms. The preservation of the materials and methods of such computational experiments with clear annotations is essential for understanding an experiment, and this is increasingly recognized in the bioinformatics community. Our assumption is that offering means of digital, structured aggregation and annotation of the objects of an experiment will provide necessary meta-data for a scientist to understand and recreate the results of an experiment. To support this we explored a model for the semantic description of a workflow-centric Research Object (RO), where an RO is defined as a resource that aggregates other resources, e.g., datasets, software, spreadsheets, text, etc. We applied this model to a case study where we analysed human metabolite variation by workflows. Results: We present the application of the workflow-centric RO model for our bioinformatics case study. Three workflows were produced following recently defined Best Practices for workflow design. By modelling the experiment as an RO, we were able to automatically query the experiment and answer questions such as “which particular data was input to a particular workflow to test a particular hypothesis?”, and “which particular conclusions were drawn from a particular workflow?”. Conclusions: Applying a workflow-centric RO model to aggregate and annotate the resources used in a bioinformatics experiment, allowed us to retrieve the conclusions of the experiment in the context of the driving hypothesis, the executed workflows and their input data. The RO model is an extendable reference model that can be used by other systems as well.

Neural basis of lexical-semantic processing and integration of symbolic gestures with words

Three studies investigated the relation between symbolic gestures and words, aiming at discover the neural basis and behavioural features of the lexical semantic processing and integration of the two communicative signals. The first study aimed at determining whether elaboration of communicative signals (symbolic gestures and words) is always accompanied by integration with each other and, if present, this integration can be considered in support of the existence of a same control mechanism. Experiment 1 aimed at determining whether and how gesture is integrated with word. Participants were administered with a semantic priming paradigm with a lexical decision task and pronounced a target word, which was preceded by a meaningful or meaningless prime gesture. When meaningful, the gesture could be either congruent or incongruent with word meaning. Duration of prime presentation (100, 250, 400 ms) randomly varied. Voice spectra, lip kinematics, and time to response were recorded and analyzed. Formant 1 of voice spectra, and mean velocity in lip kinematics increased when the prime was meaningful and congruent with the word, as compared to meaningless gesture. In other words, parameters of voice and movement were magnified by congruence, but this occurred only when prime duration was 250 ms. Time to response to meaningful gesture was shorter in the condition of congruence compared to incongruence. Experiment 2 aimed at determining whether the mechanism of integration of a prime word with a target word is similar to that of a prime gesture with a target word. Formant 1 of the target word increased when word prime was meaningful and congruent, as compared to meaningless congruent prime. Increase was, however, present for whatever prime word duration. In the second study, experiment 3 aimed at determining whether symbolic prime gesture comprehension makes use of motor simulation. Transcranial Magnetic Stimulation was delivered to left primary motor cortex 100, 250, 500 ms after prime gesture presentation. Motor Evoked Potential of First Dorsal Interosseus increased when stimulation occurred 100 ms post-stimulus. Thus, gesture was understood within 100ms and integrated with the target word within 250 ms. Experiment 4 excluded any hand motor simulation in order to comprehend prime word. The effect of the prior presentation of a symbolic gesture on congruent target word processing was investigated in study 3. In experiment 5, symbolic gestures were presented as primes, followed by semantically congruent target word or pseudowords. In this case, lexical-semantic decision was accompanied by a motor simulation at 100ms after the onset of the verbal stimuli. Summing up, the same type of integration with a word was present for both prime gesture and word. It was probably subsequent to understanding of the signal, which used motor simulation for gesture and direct access to semantics for words. However, gesture and words could be understood at the same motor level through simulation if words were preceded by an adequate gestural context. Results are discussed in the prospective of a continuum between transitive actions and emblems, in parallelism with language; the grounded/symbolic content of the different signals evidences relation between sensorimotor and linguistic systems, which could interact at different levels.

A general proposal to multilingual information access based on syntactic-semantic patterns

In the last few years, there has been a wide development in the research on textual information systems. The goal is to improve these systems in order to allow an easy localization, treatment and access to the information stored in digital format (Digital Databases, Documental Databases, and so on). There are lots of applications focused on information access (for example, Web-search systems like Google or Altavista). However, these applications have problems when they must access to cross-language information, or when they need to show information in a language different from the one of the query. This paper explores the use of syntactic-sematic patterns as a method to access to multilingual information, and revise, in the case of Information Retrieval, where it is possible and useful to employ patterns when it comes to the multilingual and interactive aspects. On the one hand, the multilingual aspects that are going to be studied are the ones related to the access to documents in different languages from the one of the query, as well as the automatic translation of the document, i.e. a machine translation system based on patterns. On the other hand, this paper is going to go deep into the interactive aspects related to the reformulation of a query based on the syntactic-semantic pattern of the request.

A semantic framework for textual data enrichment

In this work we present a semantic framework suitable of being used as support tool for recommender systems. Our purpose is to use the semantic information provided by a set of integrated resources to enrich texts by conducting different NLP tasks: WSD, domain classification, semantic similarities and sentiment analysis. After obtaining the textual semantic enrichment we would be able to recommend similar content or even to rate texts according to different dimensions. First of all, we describe the main characteristics of the semantic integrated resources with an exhaustive evaluation. Next, we demonstrate the usefulness of our resource in different NLP tasks and campaigns. Moreover, we present a combination of different NLP approaches that provide enough knowledge for being used as support tool for recommender systems. Finally, we illustrate a case of study with information related to movies and TV series to demonstrate that our framework works properly.

How many meanings for ‘may’? The case for modal polysemy

The standard Kratzerian analysis of modal auxiliaries, such as ‘may’ and ‘can’, takes them to be univocal and context-sensitive. Our first aim is to argue for an alternative view, on which such expressions are polysemous. Our second aim is to thereby shed light on the distinction between semantic context-sensitivity and polysemy. To achieve these aims, we examine the mechanisms of polysemy and context-sensitivity and provide criteria with which they can be held apart. We apply the criteria to modal auxiliaries and show that the default hypothesis should be that they are polysemous, and not merely context-sensitive. We then respond to arguments against modal ambiguity (and thus against polysemy). Finally, we show why modal polysemy has significant philosophical implications.

Cognitive fit between conceptual schemas and internal problem representations: The case of geospatio-temporal conceptual schema comprehension

Geospatio-temporal conceptual models provide a mechanism to explicitly represent geospatial and temporal aspects of applications. Such models, which focus on both what and when/where, need to be more expressive than conventional conceptual models (e.g., the ER model), which primarily focus on what is important for a given application. In this study, we view conceptual schema comprehension of geospatio-temporal data semantics in terms of matching the external problem representation (that is, the conceptual schema) to the problem-solving task (that is, syntactic and semantic comprehension tasks), an argument based on the theory of cognitive fit. Our theory suggests that an external problem representation that matches the problem solver's internal task representation will enhance performance, for example, in comprehending such schemas. To assess performance on geospatio-temporal schema comprehension tasks, we conducted a laboratory experiment using two semantically identical conceptual schemas, one of which mapped closely to the internal task representation while the other did not. As expected, we found that the geospatio-temporal conceptual schema that corresponded to the internal representation of the task enhanced the accuracy of schema comprehension; comprehension time was equivalent for both. Cognitive fit between the internal representation of the task and conceptual schemas with geospatio-temporal annotations was, therefore, manifested in accuracy of schema comprehension and not in time for problem solution. Our findings suggest that the annotated schemas facilitate understanding of data semantics represented on the schema.

Leximancer concept mapping of patient case studies

Quantitative databases are limited to information identified as important by their creators, while databases containing natural language are limited by our ability to analyze large unstructured bodies of text. Leximancer is a tool that uses semantic mapping to develop concept maps from natural language. We have applied Leximancer to educational based pathology case notes to demonstrate how real patient records or databases of case studies could be analyzed to identify unique relationships. We then discuss how such analysis could be used to conduct quantitative analysis from databases such as the Coronary Heart Disease Database.

Semantic properties of μ-charts

μ-Charts are a Statechart-like language which is designed for specifying reactive systems. This paper extends the language of μ-charts with a new parallel operator; it defines a formal semantics for the language, and then it explores the semantic properties of the extended language. The paper concludes with a simple case study to illustrate how the language may be used to specify and reason about reactive systems.

AKTive Food:semantic web based knowledge conduits for the organic food industry

We present a vision and a proposal for using Semantic Web technologies in the organic food industry. This is a very knowledge intensive industry at every step from the producer, to the caterer or restauranteur, through to the consumer. There is a crucial need for a concept of environmental audit which would allow the various stake holders to know the full environmental impact of their economic choices. This is a di?erent and parallel form of knowledge to that of price. Semantic Web technologies can be used e?ectively for the calculation and transfer of this type of knowledge (together with other forms of multimedia data) which could contribute considerably to the commercial and educational impact of the organic food industry. We outline how this could be achieved as our essential ob jective is to show how advanced technologies could be used to both reduce ecological impact and increase public awareness.

What nominal phrases are all about: the atypical case of indefinite pronouns with a determiner

This paper presents novel data that challenge the traditional categorial understanding of the nominal phrase. The established use of an indefinite pronoun with a determiner in French (ce quelqu'un, du n'importe quoi, un je ne sais quoi) contravenes assumptions both about pronouns, which should not be embedded, and nominal phrases, which should be headed by a noun. Analysed here for the first time, the embedding of a pronoun under a determiner is shown to find its justification in the semantic import of the construction. The anaphoric role guaranteeing referential continuity is promoted by a strong determiner; weak determiners typically contribute to constructing a designative use of the pronoun when a more precise characterisation cannot or will not be provided. How this construction would be analysed in the Minimalist Programme is presented to suggest that the phrase satisfies semantic requirements, which resolves the paradoxes of its traditional definition

The role of pragmatics for grammatical change: the case of preverbal non

What is the role of pragmatics in the evolution of grammatical paradigms? It is to maintain marked candidates that may come to be the default expression. This perspective is validated by the Jespersen cycle, where the standard expression of sentential negation is renewed as pragmatically marked negatives achieve default status. How status changes are effected, however, remains to be documented. This is what is achieved in this paper that looks at the evolution of preverbal negative non in Old and Middle French. The negative, which categorically marks pragmatic activation (Dryer 1996) with finite verbs in Old French, loses this value when used with non-finite verbs in Middle French. This process is accompanied by competing semantic reanalyses of the distribution of infinitives negated in this way, and by the co-occurrence with a greater lexical variety of verbs. The absence of pragmatic contribution should lead the marker to take on the role of default, which is already fulfilled by a well-established ne ... pas, pushing non to decline. Hard empirical evidence is thus provided that validates the assumed role of pragmatics in the Jespersen cycle, supporting the general view of pragmatics as supporting alternative candidates that may or may not achieve default status in the evolution of a grammatical paradigm.

Describing and communicating uncertainty within the semantic web

The Semantic Web relies on carefully structured, well defined, data to allow machines to communicate and understand one another. In many domains (e.g. geospatial) the data being described contains some uncertainty, often due to incomplete knowledge; meaningful processing of this data requires these uncertainties to be carefully analysed and integrated into the process chain. Currently, within the SemanticWeb there is no standard mechanism for interoperable description and exchange of uncertain information, which renders the automated processing of such information implausible, particularly where error must be considered and captured as it propagates through a processing sequence. In particular we adopt a Bayesian perspective and focus on the case where the inputs / outputs are naturally treated as random variables. This paper discusses a solution to the problem in the form of the Uncertainty Markup Language (UncertML). UncertML is a conceptual model, realised as an XML schema, that allows uncertainty to be quantified in a variety of ways i.e. realisations, statistics and probability distributions. UncertML is based upon a soft-typed XML schema design that provides a generic framework from which any statistic or distribution may be created. Making extensive use of Geography Markup Language (GML) dictionaries, UncertML provides a collection of definitions for common uncertainty types. Containing both written descriptions and mathematical functions, encoded as MathML, the definitions within these dictionaries provide a robust mechanism for defining any statistic or distribution and can be easily extended. Universal Resource Identifiers (URIs) are used to introduce semantics to the soft-typed elements by linking to these dictionary definitions. The INTAMAP (INTeroperability and Automated MAPping) project provides a use case for UncertML. This paper demonstrates how observation errors can be quantified using UncertML and wrapped within an Observations & Measurements (O&M) Observation. The interpolation service uses the information within these observations to influence the prediction outcome. The output uncertainties may be encoded in a variety of UncertML types, e.g. a series of marginal Gaussian distributions, a set of statistics, such as the first three marginal moments, or a set of realisations from a Monte Carlo treatment. Quantifying and propagating uncertainty in this way allows such interpolation results to be consumed by other services. This could form part of a risk management chain or a decision support system, and ultimately paves the way for complex data processing chains in the Semantic Web.